{"id":"W3214476327","doi":"10.3390/sym13112166","title":"Software Defect Prediction Using Wrapper Feature Selection Based on Dynamic Re-Ranking Strategy","year":2021,"lang":"en","type":"article","venue":"Symmetry","topic":"Software Engineering Research","field":"Computer Science","cited_by":32,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"Yayasan UTP; Universiti Teknologi Petronas","keywords":"Computer science; Feature selection; Overfitting; Data mining; Maxima and minima; Curse of dimensionality; Machine learning; Ranking (information retrieval); Artificial intelligence; Software; Classifier (UML); Feature (linguistics); Process (computing); Pattern recognition (psychology); Artificial neural network; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003461257,0.0001732341,0.0001463183,0.000317156,0.0001947498,0.0002317784,0.0003115135,0.0001731466,0.00002443335],"category_scores_gemma":[0.0006258843,0.0001823705,0.000118724,0.00170534,0.0000167889,0.0002986204,0.00008841999,0.0005239551,0.0000202055],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000353722,"about_ca_system_score_gemma":0.0002792727,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001523567,"about_ca_topic_score_gemma":0.000009494245,"domain_scores_codex":[0.9982117,0.000126884,0.0001377477,0.0005643984,0.0005658538,0.0003933909],"domain_scores_gemma":[0.9987521,0.0004331243,0.00004037022,0.0005110238,0.0001715055,0.00009190581],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00006243577,0.0003777609,0.2115975,0.0004966399,0.0002165244,0.0003826673,0.0002751772,0.6371608,0.0303649,0.001425231,0.002910895,0.1147294],"study_design_scores_gemma":[0.0003690936,0.0001355007,0.06126774,0.0001645828,0.00001349805,0.00005985654,0.00001690527,0.9317654,0.005508644,0.0002461524,0.0002157126,0.0002368619],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1720594,0.0002425689,0.8260301,0.0001103444,0.0005937755,0.0001194948,0.000006484367,0.0006946831,0.0001430653],"genre_scores_gemma":[0.9397394,0.000003813233,0.05985603,0.0001065844,0.0000993889,0.000008794653,0.00001839994,0.00002925936,0.0001383008],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.76768,"threshold_uncertainty_score":0.7436851,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01617267138903952,"score_gpt":0.27165605243976,"score_spread":0.2554833810507205,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}